The question, what works best, the intuition of expert decision-makers (Naturalistic Decision Making) or a statistical prediction algorithmic approach (Heuristics and Biases).

The answer of course, it depends on the context.

Intuition (which is presented as a form of pattern recognition) works well when the context include clear and consistent patterns and the experts has ample opportunities to practice recognition.

Where simple and valid clues exist, humans will find them given sufficient experience and enough rapid feedback. (p. 523)

This expert pattern recognition type of decision-making is especially relevant when time is a factor like in nursing or firefighting. In situations where there are contra-indications, an algorithmic would be warranted, but the authors note there may be a potential for push back from practitioners.

An important point here is that an evidence-based approach is portraited not a simplistic application of science, but rather the development of a specific practice oriented algorithm – an scientific extenuation of the practice.

Contra-indications for a naturalistic decision-making process would include:

weak or difficult to detect patterns (e.g. high ceiling effects),

the lack of feedback,

feedback over long time periods or situations involving wicked problems where the feedback is misleading.

Contra-indications for a hubristic algorithmic approach include:

a lack of adequate knowledge about relevant variables,

reliable criterion,

a body of similar cases,

a cost benefit ratio that allow for algorithm development,

a low likelihood of changing conditions that would render the algorithm obsolete

The authors also note that algorithmic approaches should be closely monitored for changing conditions.

My take: Kahneman and Klein set up their discussion as a debate between themselves and discuss different approaches primarily as an either or choice. I value their clarifications, but I would like to think of the many other situations where algorithms would be appropriate to supplementing not replacing naturalistic decision-making. For instance, they use nursing diagnoses as an example of a reliable intuition space. In some situations it is appropriate to use it, however diagnosis is a complex tasks that can include a large amount of data that can be combined in different ways. I’ll have to look at the literature to see if there is a contra-example for naturalistic decision-making. I’m not saying that naturalistic decision-making is inappropriate in many situations, only that they seem to be short changing algorithmic approaches. There are also indications that these to authors are not sharing a philosophical heuristic framework. My bet is that the positivist side is overstating naturalistic bias (which mean failing to see their own) and the naturalistic side is ignoring sources of bias when is suits them (throwing our the scientific baby with the bath water). Again this is pointing to a need for a framework that can being people with different perspective into true communication and exchange.